Particle dispersion models (PDMs) are essential to capture the influence of unresolved turbulent eddies on particle transport in computational fluid dynamics (CFD) simulations. However, the validation of these models remains challenging, especially w...
Background/Objectives: Cardiovascular and pulmonary diseases are leading comorbidities n individuals with Down syndrome (DS). Although clinically well described, preclinical models fully characterizing these cardiopulmonary alterations are lacking. O...
The increasing complexity and volume of cyberattacks present a significant challenge to traditional intrusion detection and prevention systems. One prevalent attack is domain name server (DNS) cache poisoning, which involves injecting falsified infor...
Diabetes prevalence is constantly increasing and, nowadays, it affects more than 350 million people worldwide. Therefore, the prevalence of diabetic nephropathy (DN) has also increased, becoming the main cause of end-stage renal disease (ESRD) in the...
Viscoelasticity drag-reducing flow by polymer solution can reduce pumping energy of pipe flow significantly. One of the simulation manners is direct numerical simulation (DNS). However, the computational time is too long to accept in engineering. Tur...
Liquid metal is widely used as the primary coolant in many advanced nuclear energy systems. Prandtl number of liquid metal is much lower than that of the conventional coolant of water or gas. Based on the Reynolds analogy, the turbulent Prandtl numbe...
Simulation of stochastic and variable sediment transport processes within models still poses a big challenge, especially in mountainous areas. Since sediment transport, including erosion and deposition, remains an unceasing problem in many areas, sed...
Particle-resolved direct numerical simulation (PR-DNS) is known to provide an accurate detailed insight into the local flow phenomena in static particle arrays. Most PR-DNS studies in literature do not account for reactions taking place inside the po...
Individuals with Down syndrome (DS) are more prone to develop severe respiratory tract infections. Although a RSV infection has a high clinical impact and severe outcome in individuals with DS, no vaccine nor effective therapeutics are available. Any...
Predictions are presented of mean values of statistical variables of large-scale turbulent flow of the widely used basic k-
This paper focusses on three main numerical methods, i.e., the Reynolds-Averaged Navier-Stokes (RANS), Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS) methods. The formulation and variation of different RANS methods are evaluated....
Infantile spasms are common in Down Syndrome (DS), but the mechanisms by which DS predisposes to this devastating epilepsy syndrome are unclear. In general, neuronal excitability and therefore seizure predisposition results from an imbalance of excit...
Mathematical modeling is the most important tool for constructing theories of different kinds of two-phase flows. This review is devoted to the analysis of the introduction of mathematical modeling to two-phase flows, where solid particles mainly ser...
One of the key factors in simulating realistic wall-bounded flows at high Reynolds numbers is the selection of an appropriate turbulence model for the steady Reynolds Averaged Navier–Stokes equations (RANS) equations. In this investigation, the...
The advent of the smart home, fueled by the rapid emergence of tiny embedded IoT devices and sensors, brings the consideration of space and location information to the forefront of service discovery. In a smart home environment, spaces often have com...
The traditional way to model the statistics of turbulent flow and dispersion is through averaged conservation equations, in which the turbulent transport terms are described by semi-empirical expressions. A new development has been reported by Brouwe...
Solid particles immersed in a fluid can be found in many engineering, environmental or medical fields. Applications are suspensions, sedimentation processes or procedural processes in the production of medication, food or construction materials. Whil...
Addressing the noise in seismic signals, a prevalent challenge within seismic signal processing, has been the focus of extensive research. Conventional algorithms for seismic signal denoising often fall short due to their reliance on manually determi...
SecuriDN v.
Down syndrome (DS), a major genetic cause of intellectual disability, is characterized by numerous neurodevelopmental defects. Previous in vitro studies highlighted a relationship between bioenergetic dysfunction and reduced neurogenesis in progenito...
In this paper, we investigate the feasibility of using DNS data and machine learning algorithms to assist RANS turbulence model development. High-fidelity DNS data are generated with the incompressible Navier–Stokes solver implemented in the spectral...
Down syndrome (DS), which results from the complete or partial trisomy of chromosome 21 (trisomy-21), is the most common genetically defined cause of intellectual disability. Trisomy-21 also produces, or is associated with, many neurodevelopmental ph...
Huntington’s disease (HD) is caused by the expansion of a polyglutamine (polyQ)-encoding tract in exon 1 of the huntingtin gene to greater than 35 CAG repeats. It typically has a disease course lasting 15–20 years, and there are currently...
Background/Objectives: Down syndrome (DS) is the most common cause of early-onset Alzheimer’s disease (AD). Dietary choline has been proposed as a modifiable factor to improve the cognitive and pathological outcomes of AD and DS, especially as...
Low- and high-speed streaks (ejection, Q2, and sweep, Q4, events in quadrant analysis) are significant features of coherent structures in turbulent flow. Streak formation is closely related to turbulent structures in several vortex models, such as at...
Down syndrome (DS) is a genetically-based disease based on the trisomy of chromosome 21 (Hsa21). DS is characterized by intellectual disability in association with several pathological traits among which early aging and altered motor coordination are...
Generating energy from combustion is prone to pollutant formation. In energy systems working under non-premixed combustion mode, rapid mixing is required to increase the heat release rates. However, local extinction and re-ignition may occur, resulti...
A stand-alone machine learned turbulence model is developed and applied for the solution of steady and unsteady boundary layer equations, and issues and constraints associated with the model are investigated. The results demonstrate that an accuratel...
The present study provides an extensive analysis on the hydrodynamics induced by a vertical slender pile under wave action. The authors carried out the study both experimentally and numerically, thus enabling a deep understanding of the flow physics....
This work deals with the numerical solution of hypersonic flow of viscous fluid over a compressible ramp. The solved case involves very important and complicated phenomena such as the interaction of the shock wave with the boundary layer or the trans...
A Domain Generation Algorithm (DGA) employs botnets to generate domain names through a communication link between the C&C server and the bots. A DGA can generate pseudo-random AGDs (algorithmically generated domains) regularly, a handy method for...
Diabetic nephropathy (DN) is a common complication of diabetes. DN progresses to end-stage renal disease, which has a high mortality rate. Current research is focused on identifying non-invasive potential biomarkers in the early stage of DN. We previ...
In this paper, we examined and compared the forecast performances of the dynamic Nelson–Siegel (DNS), dynamic Nelson–Siegel–Svensson (DNSS), and arbitrage-free Nelson–Siegel (AFNS) models after the financial crisis period. The...
Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. After development of DN, patients will progress to end-stage renal disease, which is associated with high morbidity and mortality. Here, we developed early-stage...
Diabetic nephropathy (DN) is the most serious complication of diabetes and a leading cause of kidney failure and mortality in patients with diabetes. However, the exact pathogenic mechanisms involved are poorly understood. Impaired mitochondrial func...
Diabetic nephropathy (DN) is a crucial metabolic health problem. The renin–angiotensin system (RAS) is well known to play an important role in DN. Abnormal RAS activity can cause the over-accumulation of angiotensin II (Ang II). Angiotensin-con...
With the increasing frequency of extreme weather events such as heavy rainstorm disasters, the stable operation of power systems is facing significant challenges. This paper proposes a two-stage restoration strategy for the distribution networks (DNs...
Background: The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the “COVLIAS 2....
Flexible resources, including district heat networks (DHN) and battery energy storage systems (BESS), can provide flexible regulation capability for distribution networks (DN), thereby increasing the absorption capacity for renewable energy. In order...
Diabetic nephropathy (DN) is one of the most significant microvascular complications in diabetic patients. DN is the leading cause of end-stage renal disease, accounting for approximately 50% of incident cases. The current treatment options, such as...
Diabetic neuropathy (DN) is characterized by nerve damage as a consequence of diabetes mellitus. Diabetes causes high blood glucose and triglyceride levels, which destroy the nerve blood vessels over time and trigger DN. Peripheral neuropathy is the...
The access of a high proportion of photovoltaic (PV) will change the energy structure of the distribution network (DN), resulting in a series of safety operation risks. This paper proposes a two-stage PV hosting capacity (PVHC) calculation model to a...
Distribution network scheduling (DNS) is the basis for distribution network management, which is computed in a periodical way via solving the formulated mixed-integer programming (MIP). To achieve the online scheduling, a provably robust learn-to-opt...
The early detection of diabetic nephropathy (DN) in mice is necessary for the development of drugs and functional foods. The purpose of this study was to identify genes that are significantly upregulated in the early stage of DN progression and devel...
Parkinson’s disease (PD) is characterized by degeneration of nigrostriatal dopaminergic neurons (DNs) and movement disorders. Low efficiency of pharmacotherapy requires improvement, e.g., using receptor agonists or antagonists as drugs. Our wor...
Background: Non-adherence with immunosuppressant medication (MNA) fosters development of de novo donor-specific antibodies (dnDSA), rejection, and graft failure (GF) in kidney transplant recipients (KTRs). However, there is no simple tool to assess M...
Diabetic nephropathy (DN) is one of the most devastating diabetic microvascular complications. It has previously been observed that iron metabolism levels are abnormal in diabetic patients. However, the mechanism by which iron metabolism levels affec...
Background: The aim of our study was to evaluate the association of angiopoietin 2 (ANGPT2) rs2442598 and vascular endothelial growth factor A (VEGFA) rs2010963 with diabetic nephropathy (DN) in Slovenian subjects with type 2 diabetes mellitus (T2DM)...
Diabetic nephropathy (DN) is a microvascular complication of type 2 diabetes mellitus (T2DM) that develops after years of T2DM and affects approximately one in four diabetic patients. Thioredoxin (TXN), thioredoxin reductase (TXNRD), and thioredoxin-...
The electric power industry sector has become increasingly aware of how counterproductive voltage sag affects distribution network systems (DNS). The voltage sag backfires disastrously at the demand load side and affects equipment in DNS. To settle t...
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